yochengliu / awesome-point-cloud-analysis Goto Github PK
View Code? Open in Web Editor NEWA list of papers and datasets about point cloud analysis (processing)
A list of papers and datasets about point cloud analysis (processing)
If you are looking for EMD of dense point clouds (with over 10,000 points) and large batch size, please check our implementation: https://github.com/Colin97/MSN-Point-Cloud-Completion
Thanks for your great works about collection and summary, I had seen that PVCNN( Point-Voxel CNN for Efficient 3D Deep Learning) was released in https://github.com/mit-han-lab/pvcnn so you can update that.
Thank you for your sharing. I think this paper 3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions and the dataset is also worth noticing.
Recently, we have released a lightweight Cylinder3D model with much higher performance here. In this codebase, the reproduced Cylinder3D model is 2.9 point higher than the original Cylinder3D model in SemanticKITTI test set (single-scan). Besides, the released models achieve competitive performance in three benchmarks, i.e., ranks 1st in Waymo 3D Semantic Segmentation Challenge, ranks 1st in SemanticKITTI LiDAR Semantic Segmentation Challenge (single-scan) and ranks 2nd in SemanticKITTI LiDAR Semantic Segmentation Challenge (multi-scan). The trained model has been used in one NeurIPS 2022 submission! More LiDAR semantic segmentation models will be supported in the future. Do not hesitate to use the trained models!
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